{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "32cd7e63-1124-4ada-96df-892798280306",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overall RMSE: 0.9925859460288985\n",
      "Overall MAE: 0.7562613430127042\n",
      "Overall R²: 0.8736361283196069\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.signal import savgol_filter, cheby2, filtfilt, find_peaks\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "import os\n",
    "\n",
    "# Define the Chebyshev Type II filter function\n",
    "def chebyshev_type_ii_filter(raw_ppg, order=5, fs=100, fL=0.5, fH=5.0):\n",
    "    Fn = fs / 2  # Nyquist frequency\n",
    "    b, a = cheby2(order, 20, [fL / Fn, fH / Fn], btype='band')\n",
    "    return filtfilt(b, a, raw_ppg)\n",
    "\n",
    "# Main function to process and estimate respiration rate\n",
    "def estimate_respiration_rate(df_data, start_time=0, end_time=None, peak_threshold=0.5, min_peak_distance=3.5):\n",
    "    # Extract the PPG data from the DataFrame\n",
    "    ppg_IRdata = df_data[\"PPG_IR\"]\n",
    "    ppg_REDdata = df_data[\"PPG_RED\"]\n",
    "    \n",
    "    # Create a time axis (assuming constant sampling rate)\n",
    "    sampling_rate = 100  # Adjust to your actual sampling rate\n",
    "    num_points = len(ppg_IRdata)\n",
    "    time = np.arange(0, num_points) / sampling_rate\n",
    "\n",
    "    # Handle the end time, default to the length of the signal\n",
    "    if end_time is None or end_time > num_points / sampling_rate:\n",
    "        end_time = num_points / sampling_rate\n",
    "\n",
    "    # Convert start_time and end_time to indices for slicing\n",
    "    start_idx = int(start_time * sampling_rate)\n",
    "    end_idx = int(end_time * sampling_rate)\n",
    "\n",
    "    # Apply Chebyshev Type II filter to both PPG IR and RED signals\n",
    "    ppg_IR_filtered = chebyshev_type_ii_filter(ppg_IRdata)\n",
    "    ppg_RED_filtered = chebyshev_type_ii_filter(ppg_REDdata)\n",
    "\n",
    "    # Apply Savitzky-Golay filter after the Chebyshev filter\n",
    "    window_size = 21  # Adjust as needed\n",
    "    poly_order = 3  # Adjust as needed\n",
    "    ppg_IR_smooth = savgol_filter(ppg_IR_filtered, window_size, poly_order)\n",
    "    ppg_RED_smooth = savgol_filter(ppg_RED_filtered, window_size, poly_order)\n",
    "\n",
    "    # Apply a moving average filter to both PPG signals\n",
    "    window_size = 40  # Adjust the window size as needed\n",
    "    ppg_IRdata_ma = np.convolve(ppg_IR_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "    ppg_REDdata_ma = np.convolve(ppg_RED_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "\n",
    "  # Find peaks in the PPG signals\n",
    "    peaks_IR, _ = find_peaks(ppg_IRdata_ma, height=0)\n",
    "    peaks_RED, _ = find_peaks(ppg_REDdata_ma, height=0)\n",
    "\n",
    "     # Calculate the peak tip locations\n",
    "    peak_tips_IR = np.array([peaks_IR, ppg_IRdata_ma[peaks_IR]]).T\n",
    "    peak_tips_RED = np.array([peaks_RED, ppg_REDdata_ma[peaks_RED]]).T\n",
    "\n",
    "    # Identify systolic peaks (adjust the threshold as needed)\n",
    "    systolic_peaks_IR = peak_tips_IR[peak_tips_IR[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "    systolic_peaks_RED = peak_tips_RED[peak_tips_RED[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "\n",
    "    # Set the minimum distance between peaks to remove nearby small peaks\n",
    "    peaks_IR = find_peaks(systolic_peaks_IR[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "    peaks_RED = find_peaks(systolic_peaks_RED[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "\n",
    "    # Calculate the BPM for IR and RED signals using the total duration\n",
    "    total_duration = num_points / sampling_rate\n",
    "    respiration_rate_IR = (len(peaks_IR) / total_duration) * 60\n",
    "    respiration_rate_RED = (len(peaks_RED) / total_duration) * 60\n",
    "\n",
    "    # Average respiration rate based on both IR and RED signals\n",
    "    estimated_rr = (respiration_rate_IR + respiration_rate_RED) / 2\n",
    "\n",
    "    return estimated_rr\n",
    "\n",
    "# Function to process a folder of CSV files and calculate overall metrics\n",
    "def process_files(folder_path):\n",
    "    results = []\n",
    "    actual_rrs = []\n",
    "    estimated_rrs = []\n",
    "\n",
    "    for file in os.listdir(folder_path):\n",
    "        if file.endswith(\".csv\"):\n",
    "            file_path = os.path.join(folder_path, file)\n",
    "            df_data = pd.read_csv(file_path)\n",
    "\n",
    "            # Extract the actual respiration rate from the file\n",
    "            actual_rr = df_data['Respiration Rate'].mean()  # Average actual RR from the file\n",
    "            estimated_rr = estimate_respiration_rate(df_data)\n",
    "\n",
    "            # Append to the result list\n",
    "            results.append([file, actual_rr, estimated_rr])\n",
    "\n",
    "            # Collect actual and estimated RR for error calculations\n",
    "            actual_rrs.append(actual_rr)\n",
    "            estimated_rrs.append(estimated_rr)\n",
    "\n",
    "    # Convert the result list to a DataFrame\n",
    "    results_df = pd.DataFrame(results, columns=[\"Filename\", \"Actual RR\", \"Estimated RR\"])\n",
    "\n",
    "    # Calculate overall error metrics\n",
    "    rmse = np.sqrt(mean_squared_error(actual_rrs, estimated_rrs))\n",
    "    mae = mean_absolute_error(actual_rrs, estimated_rrs)\n",
    "    r2 = r2_score(actual_rrs, estimated_rrs)\n",
    "\n",
    "    # Save the results to a CSV file\n",
    "    results_df.to_csv(\"TMCH_estimated_respiration_rates_mar25_v2.csv\", index=False)\n",
    "\n",
    "    print(f\"Overall RMSE: {rmse}\")\n",
    "    print(f\"Overall MAE: {mae}\")\n",
    "    print(f\"Overall R²: {r2}\")\n",
    "\n",
    "# Specify the folder containing your CSV files\n",
    "folder_path = \"TMNI_Dataset_Respiration/data_2/\"\n",
    "\n",
    "# Process the files and calculate metrics\n",
    "process_files(folder_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "88c446cc-602d-4521-bb83-b45576b31ae2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda4\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "C:\\ProgramData\\anaconda4\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BIDMC SNR Statistics:\n",
      "count    53.000000\n",
      "mean     11.977450\n",
      "std       3.016321\n",
      "min       8.517873\n",
      "25%       9.719914\n",
      "50%      10.574808\n",
      "75%      14.338965\n",
      "max      22.309020\n",
      "dtype: float64\n",
      "\n",
      "TMCH SNR Statistics:\n",
      "count    551.000000\n",
      "mean      35.066578\n",
      "std        6.247017\n",
      "min        4.979732\n",
      "25%       31.518249\n",
      "50%       35.593034\n",
      "75%       39.052076\n",
      "max       50.410617\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Function to compute Signal-to-Noise Ratio (SNR)\n",
    "def compute_snr(signal):\n",
    "    signal_power = np.mean(signal ** 2)\n",
    "    noise_power = np.var(signal)\n",
    "    snr = 10 * np.log10(signal_power / noise_power)\n",
    "    return snr\n",
    "\n",
    "# BIDMC Dataset\n",
    "folder_path_bidmc = 'BIDMC_Dataset/data'\n",
    "bidmc_snr_values = []\n",
    "\n",
    "for file in os.listdir(folder_path_bidmc):\n",
    "    if file.endswith('_Signals.csv'):\n",
    "        signals_path = os.path.join(folder_path_bidmc, file)\n",
    "        data = pd.read_csv(signals_path)\n",
    "        \n",
    "        if ' PLETH' in data.columns:\n",
    "            ppg_signal = data[' PLETH']  # Adjust column name if necessary\n",
    "            bidmc_snr_values.append(compute_snr(ppg_signal))\n",
    "\n",
    "# TMCH Dataset\n",
    "folder_path_tmch = \"TMNI_Dataset_Respiration/data_2/\"\n",
    "tmch_snr_values = []\n",
    "\n",
    "for file in os.listdir(folder_path_tmch):\n",
    "    if file.endswith('.csv'):\n",
    "        signals_path = os.path.join(folder_path_tmch, file)\n",
    "        df_data = pd.read_csv(signals_path)\n",
    "        \n",
    "        if \"PPG_IR\" in df_data.columns:\n",
    "            ppg_IRdata = df_data[\"PPG_IR\"]\n",
    "            tmch_snr_values.append(compute_snr(ppg_IRdata))\n",
    "\n",
    "# Compare SNR Distributions\n",
    "sns.histplot(bidmc_snr_values, bins=20, kde=True, color='blue', label='BIDMC')\n",
    "sns.histplot(tmch_snr_values, bins=20, kde=True, color='green', label='TMCH')\n",
    "plt.legend()\n",
    "plt.title(\"SNR Comparison: BIDMC vs TMCH\")\n",
    "plt.xlabel(\"SNR (dB)\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.show()\n",
    "\n",
    "# Print Summary Statistics\n",
    "print(\"BIDMC SNR Statistics:\")\n",
    "print(pd.Series(bidmc_snr_values).describe())\n",
    "print(\"\\nTMCH SNR Statistics:\")\n",
    "print(pd.Series(tmch_snr_values).describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "567e005c-67f8-43c3-a50c-5729491453a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda4\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\anaconda4\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BIDMC SNR Statistics:\n",
      "count    53.000000\n",
      "mean     11.977450\n",
      "std       3.016321\n",
      "min       8.517873\n",
      "25%       9.719914\n",
      "50%      10.574808\n",
      "75%      14.338965\n",
      "max      22.309020\n",
      "dtype: float64\n",
      "\n",
      "TMCH SNR Statistics:\n",
      "count    560.000000\n",
      "mean      34.601737\n",
      "std        6.218133\n",
      "min        6.292333\n",
      "25%       30.910435\n",
      "50%       35.088450\n",
      "75%       38.624904\n",
      "max       55.254961\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Function to compute Signal-to-Noise Ratio (SNR)\n",
    "def compute_snr(signal):\n",
    "    signal_power = np.mean(signal ** 2)\n",
    "    noise_power = np.var(signal)\n",
    "    snr = 10 * np.log10(signal_power / noise_power)\n",
    "    return snr\n",
    "\n",
    "# BIDMC Dataset\n",
    "folder_path_bidmc = 'BIDMC_Dataset/data'\n",
    "bidmc_snr_values = []\n",
    "\n",
    "for file in os.listdir(folder_path_bidmc):\n",
    "    if file.endswith('_Signals.csv'):\n",
    "        signals_path = os.path.join(folder_path_bidmc, file)\n",
    "        data = pd.read_csv(signals_path)\n",
    "        \n",
    "        if ' PLETH' in data.columns:\n",
    "            ppg_signal = data[' PLETH']  # Adjust column name if necessary\n",
    "            bidmc_snr_values.append(compute_snr(ppg_signal))\n",
    "\n",
    "# TMCH Dataset\n",
    "folder_path_tmch = \"TMNI_Dataset_Respiration/data_3/\"\n",
    "tmch_snr_values = []\n",
    "\n",
    "for file in os.listdir(folder_path_tmch):\n",
    "    if file.endswith('.csv'):\n",
    "        signals_path = os.path.join(folder_path_tmch, file)\n",
    "        df_data = pd.read_csv(signals_path)\n",
    "        \n",
    "        if \" PPG IR\" in df_data.columns:\n",
    "            ppg_IRdata = df_data[\" PPG IR\"]\n",
    "            tmch_snr_values.append(compute_snr(ppg_IRdata))\n",
    "\n",
    "plt.rcParams.update({\n",
    "    'font.size': 14,       # Increase font size\n",
    "    'font.weight': 'bold', # Make text bold\n",
    "    'axes.labelweight': 'bold',  # Bold axis labels\n",
    "    'axes.titlesize': 16,  # Larger title font size\n",
    "    'axes.titleweight': 'bold', # Bold title\n",
    "    'legend.fontsize': 12,  # Legend font size\n",
    "    'xtick.labelsize': 12,  # X-axis tick font size\n",
    "    'ytick.labelsize': 12   # Y-axis tick font size\n",
    "})\n",
    "\n",
    "# Compare SNR Distributions\n",
    "plt.figure()\n",
    "sns.histplot(bidmc_snr_values, bins=20, kde=True, color='blue', label='BIDMC')\n",
    "plt.legend()\n",
    "plt.title(\"SNR Comparison: BIDMC\")\n",
    "plt.xlabel(\"SNR (dB)\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.show()\n",
    "plt.savefig(\"BIDMC_SNR_Comparison.png\", dpi=300, bbox_inches='tight')\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "sns.histplot(tmch_snr_values, bins=20, kde=True, color='green', label='TMCH')\n",
    "plt.legend()\n",
    "plt.title(\"SNR Comparison:TMCH\")\n",
    "plt.xlabel(\"SNR (dB)\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.show()\n",
    "plt.savefig(\"TMCH_SNR_Comparison.png\", dpi=300, bbox_inches='tight')\n",
    "\n",
    "\n",
    "# Print Summary Statistics\n",
    "print(\"BIDMC SNR Statistics:\")\n",
    "print(pd.Series(bidmc_snr_values).describe())\n",
    "print(\"\\nTMCH SNR Statistics:\")\n",
    "print(pd.Series(tmch_snr_values).describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5bbad236-e53a-4f5a-b1c9-73606d534f4a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overall RMSE: 0.9337443895874513\n",
      "Overall MAE: 0.7347036328871893\n",
      "Overall R²: 0.8875242005363185\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.signal import savgol_filter, cheby2, filtfilt, find_peaks\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "import os\n",
    "\n",
    "# Define the Chebyshev Type II filter function\n",
    "def chebyshev_type_ii_filter(raw_ppg, order=5, fs=100, fL=0.5, fH=5.0):\n",
    "    Fn = fs / 2  # Nyquist frequency\n",
    "    b, a = cheby2(order, 20, [fL / Fn, fH / Fn], btype='band')\n",
    "    return filtfilt(b, a, raw_ppg)\n",
    "\n",
    "# Main function to process and estimate respiration rate\n",
    "def estimate_respiration_rate(df_data, start_time=0, end_time=None, peak_threshold=0.5, min_peak_distance=3.5):\n",
    "    # Extract the PPG data from the DataFrame\n",
    "    ppg_IRdata = df_data[\"PPG_IR\"]\n",
    "    ppg_REDdata = df_data[\"PPG_RED\"]\n",
    "    \n",
    "    # Create a time axis (assuming constant sampling rate)\n",
    "    sampling_rate = 100  # Adjust to your actual sampling rate\n",
    "    num_points = len(ppg_IRdata)\n",
    "    time = np.arange(0, num_points) / sampling_rate\n",
    "\n",
    "    # Handle the end time, default to the length of the signal\n",
    "    if end_time is None or end_time > num_points / sampling_rate:\n",
    "        end_time = num_points / sampling_rate\n",
    "\n",
    "    # Convert start_time and end_time to indices for slicing\n",
    "    start_idx = int(start_time * sampling_rate)\n",
    "    end_idx = int(end_time * sampling_rate)\n",
    "\n",
    "    # Apply Chebyshev Type II filter to both PPG IR and RED signals\n",
    "    ppg_IR_filtered = chebyshev_type_ii_filter(ppg_IRdata)\n",
    "    ppg_RED_filtered = chebyshev_type_ii_filter(ppg_REDdata)\n",
    "\n",
    "    # Apply Savitzky-Golay filter after the Chebyshev filter\n",
    "    window_size = 21  # Adjust as needed\n",
    "    poly_order = 3  # Adjust as needed\n",
    "    ppg_IR_smooth = savgol_filter(ppg_IR_filtered, window_size, poly_order)\n",
    "    ppg_RED_smooth = savgol_filter(ppg_RED_filtered, window_size, poly_order)\n",
    "\n",
    "    # Apply a moving average filter to both PPG signals\n",
    "    window_size = 40  # Adjust the window size as needed\n",
    "    ppg_IRdata_ma = np.convolve(ppg_IR_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "    ppg_REDdata_ma = np.convolve(ppg_RED_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "\n",
    "  # Find peaks in the PPG signals\n",
    "    peaks_IR, _ = find_peaks(ppg_IRdata_ma, height=0)\n",
    "    peaks_RED, _ = find_peaks(ppg_REDdata_ma, height=0)\n",
    "\n",
    "     # Calculate the peak tip locations\n",
    "    peak_tips_IR = np.array([peaks_IR, ppg_IRdata_ma[peaks_IR]]).T\n",
    "    peak_tips_RED = np.array([peaks_RED, ppg_REDdata_ma[peaks_RED]]).T\n",
    "\n",
    "    # Identify systolic peaks (adjust the threshold as needed)\n",
    "    systolic_peaks_IR = peak_tips_IR[peak_tips_IR[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "    systolic_peaks_RED = peak_tips_RED[peak_tips_RED[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "\n",
    "    # Set the minimum distance between peaks to remove nearby small peaks\n",
    "    peaks_IR = find_peaks(systolic_peaks_IR[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "    peaks_RED = find_peaks(systolic_peaks_RED[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "\n",
    "    # Calculate the BPM for IR and RED signals using the total duration\n",
    "    total_duration = num_points / sampling_rate\n",
    "    respiration_rate_IR = (len(peaks_IR) / total_duration) * 60\n",
    "    respiration_rate_RED = (len(peaks_RED) / total_duration) * 60\n",
    "\n",
    "    # Average respiration rate based on both IR and RED signals\n",
    "    estimated_rr = (respiration_rate_IR + respiration_rate_RED) / 2\n",
    "\n",
    "    return estimated_rr\n",
    "\n",
    "# Function to process a folder of CSV files and calculate overall metrics\n",
    "def process_files(folder_path):\n",
    "    results = []\n",
    "    actual_rrs = []\n",
    "    estimated_rrs = []\n",
    "\n",
    "    for file in os.listdir(folder_path):\n",
    "        if file.endswith(\".csv\"):\n",
    "            file_path = os.path.join(folder_path, file)\n",
    "            df_data = pd.read_csv(file_path)\n",
    "\n",
    "            # Extract the actual respiration rate from the file\n",
    "            actual_rr = df_data['Respiration Rate'].mean()  # Average actual RR from the file\n",
    "            estimated_rr = estimate_respiration_rate(df_data)\n",
    "\n",
    "            # Append to the result list\n",
    "            results.append([file, actual_rr, estimated_rr])\n",
    "\n",
    "            # Collect actual and estimated RR for error calculations\n",
    "            actual_rrs.append(actual_rr)\n",
    "            estimated_rrs.append(estimated_rr)\n",
    "\n",
    "    # Convert the result list to a DataFrame\n",
    "    results_df = pd.DataFrame(results, columns=[\"Filename\", \"Actual RR\", \"Estimated RR\"])\n",
    "\n",
    "    # Calculate overall error metrics\n",
    "    rmse = np.sqrt(mean_squared_error(actual_rrs, estimated_rrs))\n",
    "    mae = mean_absolute_error(actual_rrs, estimated_rrs)\n",
    "    r2 = r2_score(actual_rrs, estimated_rrs)\n",
    "\n",
    "    # Save the results to a CSV file\n",
    "    results_df.to_csv(\"TMCH_Estimated_RR_v5.csv\", index=False)\n",
    "\n",
    "    print(f\"Overall RMSE: {rmse}\")\n",
    "    print(f\"Overall MAE: {mae}\")\n",
    "    print(f\"Overall R²: {r2}\")\n",
    "\n",
    "# Specify the folder containing your CSV files\n",
    "folder_path = \"TMNI_Dataset_Respiration/data_4/\"\n",
    "\n",
    "# Process the files and calculate metrics\n",
    "process_files(folder_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b52e375d-3091-4b42-9db5-d927392c5d5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performance analysis completed. Results saved to 'window_performance_analysis_v5'.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.signal import savgol_filter, cheby2, filtfilt, find_peaks\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Define the Chebyshev Type II filter function\n",
    "def chebyshev_type_ii_filter(raw_ppg, order=5, fs=100, fL=0.5, fH=5.0):\n",
    "    Fn = fs / 2  # Nyquist frequency\n",
    "    b, a = cheby2(order, 20, [fL / Fn, fH / Fn], btype='band')\n",
    "    return filtfilt(b, a, raw_ppg)\n",
    "def analyze_performance(performance_df):\n",
    "    # Calculate descriptive statistics\n",
    "    descriptive_stats = performance_df.describe()\n",
    "    print(\"Descriptive Statistics:\\n\", descriptive_stats)\n",
    "\n",
    "    # Plot RMSE vs. Window Size\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    rmse_line = sns.lineplot(data=performance_df, x=\"Window Size\", y=\"RMSE\", marker='o')\n",
    "    plt.title(\"RMSE vs. Window Size\")\n",
    "    plt.xlabel(\"Window Size\")\n",
    "    plt.ylabel(\"RMSE\")\n",
    "    plt.grid()\n",
    "    \n",
    "    # Add data values to the RMSE plot\n",
    "    for x, y in zip(performance_df[\"Window Size\"], performance_df[\"RMSE\"]):\n",
    "        plt.text(x, y, f'{y:.2f}', color='black', ha='center', va='bottom')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "    # Plot MAE vs. Window Size\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    mae_line = sns.lineplot(data=performance_df, x=\"Window Size\", y=\"MAE\", marker='o', color='orange')\n",
    "    plt.title(\"MAE vs. Window Size\")\n",
    "    plt.xlabel(\"Window Size\")\n",
    "    plt.ylabel(\"MAE\")\n",
    "    plt.grid()\n",
    "    \n",
    "    # Add data values to the MAE plot\n",
    "    for x, y in zip(performance_df[\"Window Size\"], performance_df[\"MAE\"]):\n",
    "        plt.text(x, y, f'{y:.2f}', color='black', ha='center', va='bottom')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "    # Plot R² vs. Window Size\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    r2_line = sns.lineplot(data=performance_df, x=\"Window Size\", y=\"R²\", marker='o', color='green')\n",
    "    plt.title(\"R² vs. Window Size\")\n",
    "    plt.xlabel(\"Window Size\")\n",
    "    plt.ylabel(\"R²\")\n",
    "    plt.grid()\n",
    "    \n",
    "    # Add data values to the R² plot\n",
    "    for x, y in zip(performance_df[\"Window Size\"], performance_df[\"R²\"]):\n",
    "        plt.text(x, y, f'{y:.2f}', color='black', ha='center', va='bottom')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "    # Calculate the correlation matrix\n",
    "    correlation_matrix = performance_df.corr()\n",
    "    print(\"Correlation Matrix:\\n\", correlation_matrix)\n",
    "\n",
    "    # Visualize the correlation matrix\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(correlation_matrix, annot=True, fmt=\".2f\", cmap='coolwarm', square=True)\n",
    "    plt.title(\"Correlation Matrix\")\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "# Main function to process and estimate respiration rate\n",
    "def estimate_respiration_rate(df_data, window_size, start_time=0, end_time=None, peak_threshold=0.5, min_peak_distance=3.5):\n",
    "    # Extract the PPG data from the DataFrame\n",
    "    ppg_IRdata = df_data[\"PPG_IR\"]\n",
    "    ppg_REDdata = df_data[\"PPG_RED\"]\n",
    "    \n",
    "    # Create a time axis (assuming constant sampling rate)\n",
    "    sampling_rate = 100  # Adjust to your actual sampling rate\n",
    "    num_points = len(ppg_IRdata)\n",
    "    time = np.arange(0, num_points) / sampling_rate\n",
    "\n",
    "    # Handle the end time, default to the length of the signal\n",
    "    if end_time is None or end_time > num_points / sampling_rate:\n",
    "        end_time = num_points / sampling_rate\n",
    "\n",
    "    # Convert start_time and end_time to indices for slicing\n",
    "    start_idx = int(start_time * sampling_rate)\n",
    "    end_idx = int(end_time * sampling_rate)\n",
    "\n",
    "    # Apply Chebyshev Type II filter to both PPG IR and RED signals\n",
    "    ppg_IR_filtered = chebyshev_type_ii_filter(ppg_IRdata)\n",
    "    ppg_RED_filtered = chebyshev_type_ii_filter(ppg_REDdata)\n",
    "\n",
    "    # Apply Savitzky-Golay filter with the provided window size\n",
    "    poly_order = 3  # Adjust as needed\n",
    "    ppg_IR_smooth = savgol_filter(ppg_IR_filtered, window_size, poly_order)\n",
    "    ppg_RED_smooth = savgol_filter(ppg_RED_filtered, window_size, poly_order)\n",
    "\n",
    "    # Apply a moving average filter to both PPG signals\n",
    "    ppg_IRdata_ma = np.convolve(ppg_IR_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "    ppg_REDdata_ma = np.convolve(ppg_RED_filtered, np.ones((window_size,)) / window_size, mode='same')\n",
    "\n",
    "    # Find peaks in the PPG signals\n",
    "    peaks_IR, _ = find_peaks(ppg_IRdata_ma, height=0)\n",
    "    peaks_RED, _ = find_peaks(ppg_REDdata_ma, height=0)\n",
    "\n",
    "    # Calculate the peak tip locations\n",
    "    peak_tips_IR = np.array([peaks_IR, ppg_IRdata_ma[peaks_IR]]).T\n",
    "    peak_tips_RED = np.array([peaks_RED, ppg_REDdata_ma[peaks_RED]]).T\n",
    "\n",
    "    # Identify systolic peaks (adjust the threshold as needed)\n",
    "    systolic_peaks_IR = peak_tips_IR[peak_tips_IR[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "    systolic_peaks_RED = peak_tips_RED[peak_tips_RED[:, 1] > 0.6]  # Adjust the threshold (0.6) as needed\n",
    "\n",
    "    # Set the minimum distance between peaks to remove nearby small peaks\n",
    "    peaks_IR = find_peaks(systolic_peaks_IR[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "    peaks_RED = find_peaks(systolic_peaks_RED[:, 1], height=peak_threshold, distance=min_peak_distance)[0]\n",
    "\n",
    "    # Calculate the BPM for IR and RED signals using the total duration\n",
    "    total_duration = num_points / sampling_rate\n",
    "    respiration_rate_IR = (len(peaks_IR) / total_duration) * 60\n",
    "    respiration_rate_RED = (len(peaks_RED) / total_duration) * 60\n",
    "\n",
    "    # Average respiration rate based on both IR and RED signals\n",
    "    estimated_rr = (respiration_rate_IR + respiration_rate_RED) / 2\n",
    "\n",
    "    return estimated_rr\n",
    "\n",
    "# Function to process a folder of CSV files and calculate overall metrics\n",
    "def process_files(folder_path, window_sizes):\n",
    "    overall_results = []\n",
    "\n",
    "    for window_size in window_sizes:\n",
    "        results = []\n",
    "        actual_rrs = []\n",
    "        estimated_rrs = []\n",
    "\n",
    "        for file in os.listdir(folder_path):\n",
    "            if file.endswith(\".csv\"):\n",
    "                file_path = os.path.join(folder_path, file)\n",
    "                df_data = pd.read_csv(file_path)\n",
    "\n",
    "                # Extract the actual respiration rate from the file\n",
    "                actual_rr = df_data['Respiration Rate'].mean()  # Average actual RR from the file\n",
    "                estimated_rr = estimate_respiration_rate(df_data, window_size)\n",
    "\n",
    "                # Append to the result list\n",
    "                results.append([file, actual_rr, estimated_rr])\n",
    "\n",
    "                # Collect actual and estimated RR for error calculations\n",
    "                actual_rrs.append(actual_rr)\n",
    "                estimated_rrs.append(estimated_rr)\n",
    "\n",
    "        # Convert the result list to a DataFrame\n",
    "        results_df = pd.DataFrame(results, columns=[\"Filename\", \"Actual RR\", \"Estimated RR\"])\n",
    "\n",
    "        # Calculate overall error metrics\n",
    "        rmse = np.sqrt(mean_squared_error(actual_rrs, estimated_rrs))\n",
    "        mae = mean_absolute_error(actual_rrs, estimated_rrs)\n",
    "        r2 = r2_score(actual_rrs, estimated_rrs)\n",
    "\n",
    "        # Store results for this window size\n",
    "        overall_results.append([window_size, rmse, mae, r2])\n",
    "\n",
    "        # Save the results to a CSV file for this window size\n",
    "        results_df.to_csv(f\"estimated_respiration_rates_window_{window_size}.csv\", index=False)\n",
    "\n",
    "    # Create a DataFrame for overall results and save it\n",
    "    overall_results_df = pd.DataFrame(overall_results, columns=[\"Window Size\", \"RMSE\", \"MAE\", \"R²\"])\n",
    "    overall_results_df.to_csv(\"window_performance_analysis_v5.csv\", index=False)\n",
    "\n",
    "    print(\"Performance analysis completed. Results saved to 'window_performance_analysis_v5'.\")\n",
    "\n",
    "# Specify the folder containing your CSV files\n",
    "folder_path = \"TMNI_Dataset_Respiration/data_4/\"\n",
    "window_sizes = [10, 20, 30, 32,40, 50, 60,64, 70, 80, 90, 100, 110, 120]\n",
    "\n",
    "# Process the files and calculate metrics\n",
    "process_files(folder_path, window_sizes)\n",
    "\n",
    "#analyze_performance(window_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "83fbe65e-c011-4169-bda1-821846643e29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Load your CSV file\n",
    "file_path = \"window_performance_analysis_v5.csv\"  # Replace with your CSV file path\n",
    "data = pd.read_csv(file_path)\n",
    "\n",
    "# Define a function to plot each metric with specified colors and highlight the best value\n",
    "def plot_metric_with_best(x, y, metric_name, ylabel, filename, color, best_func):\n",
    "    plt.figure(figsize=(10, 6))  # Set figure size\n",
    "    \n",
    "    # Plot the line\n",
    "    plt.plot(x, y, label=metric_name, color=color, linewidth=3, marker='o', markersize=8)\n",
    "    \n",
    "    # Annotate data values\n",
    "    for i, value in enumerate(y):\n",
    "        plt.text(x[i], y[i], f'{value:.2f}', fontsize=10, ha='center', va='bottom', color='black', weight='bold')\n",
    "    \n",
    "    # Find the best value\n",
    "    best_value = best_func(y)\n",
    "    best_index = y.idxmin() if best_func == min else y.idxmax()\n",
    "    best_window_size = x[best_index]\n",
    "    \n",
    "    # Highlight the best value\n",
    "    plt.axvline(x=best_window_size, color='gold', linestyle='--', linewidth=2, label=f'Best at {best_window_size}')\n",
    "    plt.scatter(best_window_size, best_value, color='gold', s=100, label=f'Best Value: {best_value:.2f}')\n",
    "    \n",
    "    # Add labels, title, and legend\n",
    "    plt.title(f'{metric_name} vs Window Size - TMCH Dataset', fontsize=16, fontweight='bold')\n",
    "    plt.xlabel('Window Size (seconds)', fontsize=16, fontweight='bold')\n",
    "    plt.ylabel(ylabel, fontsize=16, fontweight='bold')\n",
    "    plt.grid(True, linestyle='--', alpha=0.7)\n",
    "    \n",
    "    # Customize legend\n",
    "    legend = plt.legend(fontsize=12, loc='best', frameon=True)\n",
    "    for text in legend.get_texts():\n",
    "        text.set_fontweight('bold')  # Make legend text bold\n",
    "\n",
    "    # Customize ticks\n",
    "    plt.xticks(fontsize=16, fontweight='bold')\n",
    "    plt.yticks(fontsize=16, fontweight='bold')\n",
    "    \n",
    "    # Save the plot as a high-resolution image\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(filename, dpi=600)  # Save as high-quality PNG\n",
    "    plt.grid(\n",
    "    color='gray',        # Color of the grid lines\n",
    "    linestyle='-',      # Line style (e.g., '-', '--', '-.', ':')\n",
    "    linewidth=0.9,       # Line width\n",
    "    alpha=0.9            # Transparency of the grid\n",
    "    )\n",
    "    plt.show()\n",
    "\n",
    "# Plot RMSE (min value is best, green)\n",
    "plot_metric_with_best(\n",
    "    data['Window Size (seconds)'], data['RMSE'], 'RMSE', 'RMSE Value', 't_rmse_plot_v0.png', \n",
    "    color='green', best_func=min\n",
    ")\n",
    "\n",
    "# Plot MAE (min value is best, red)\n",
    "plot_metric_with_best(\n",
    "    data['Window Size (seconds)'], data['MAE'], 'MAE', 'MAE Value', 't_mae_plot_v0.png', \n",
    "    color='red', best_func=min\n",
    ")\n",
    "\n",
    "# Plot R² (max value is best, blue)\n",
    "plot_metric_with_best(\n",
    "    data['Window Size (seconds)'], data['R2'], 'R²', 'R² Value', 't_r2_plot_v0.png', \n",
    "    color='blue', best_func=max\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1a80650a-2eea-4784-9d0a-a66ff095a3e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.9337\n",
      "MAE: 0.7347\n",
      "R²: 0.8875\n",
      "Estimated RR - Standard Deviation: 2.6707\n",
      "Estimated RR - Variance: 7.1325\n",
      "Error - Standard Deviation: 0.9336\n",
      "Error - Variance: 0.8717\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "import numpy as np\n",
    "\n",
    "# Load the CSV file into a pandas DataFrame\n",
    "df = pd.read_csv('TMCH_Estimated_RR_v5.csv')  # Replace with your file path\n",
    "\n",
    "# Extract Actual RR and Estimated RR columns\n",
    "actual_rr = df['Actual RR']  \n",
    "estimated_rr = df['Estimated RR']  \n",
    "\n",
    "# Calculate RMSE\n",
    "rmse = np.sqrt(mean_squared_error(actual_rr, estimated_rr))\n",
    "\n",
    "# Calculate MAE\n",
    "mae = mean_absolute_error(actual_rr, estimated_rr)\n",
    "\n",
    "# Calculate R²\n",
    "r2 = r2_score(actual_rr, estimated_rr)\n",
    "\n",
    "# Calculate Standard Deviation and Variance for Estimated RR\n",
    "estimated_std = np.std(estimated_rr)\n",
    "estimated_variance = np.var(estimated_rr)\n",
    "\n",
    "# Calculate Error\n",
    "error = actual_rr - estimated_rr\n",
    "\n",
    "# Calculate Error Variance and Error Standard Deviation\n",
    "error_variance = np.var(error)\n",
    "error_std = np.std(error)\n",
    "\n",
    "# Print results\n",
    "print(f'RMSE: {rmse:.4f}')\n",
    "print(f'MAE: {mae:.4f}')\n",
    "print(f'R²: {r2:.4f}')\n",
    "print(f'Estimated RR - Standard Deviation: {estimated_std:.4f}')\n",
    "print(f'Estimated RR - Variance: {estimated_variance:.4f}')\n",
    "print(f'Error - Standard Deviation: {error_std:.4f}')\n",
    "print(f'Error - Variance: {error_variance:.4f}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "35e3c8c0-916b-4564-a62d-6184a7d99cc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.9337443895874513\n",
      "MAE: 0.7347036328871893\n",
      "R²: 0.8875242005363185\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "\n",
    "# Load the CSV file into a DataFrame\n",
    "df = pd.read_csv(\"TMCH_Estimated_RR_v5.csv\")  # Replace with your actual CSV file path\n",
    "\n",
    "# Set font properties for better visualization\n",
    "plt.rcParams['font.weight'] = 'bold'  # Bold font\n",
    "plt.rcParams['axes.labelweight'] = 'bold'  # Bold labels\n",
    "plt.rcParams['axes.titleweight'] = 'bold'\n",
    "\n",
    "# 3. Scatter Plot of Actual vs Estimated RR\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(x='Actual RR', y='Estimated RR', data=df, color='purple')\n",
    "plt.plot([df['Actual RR'].min(), df['Actual RR'].max()], \n",
    "         [df['Actual RR'].min(), df['Actual RR'].max()], \n",
    "         color='red', lw=2, linestyle='--')\n",
    "\n",
    "plt.text(0.05, 0.95, f\"$R^2$ = 0.88\", fontsize=14, fontweight='bold', \n",
    "         color='black', transform=plt.gca().transAxes, \n",
    "         verticalalignment='top', horizontalalignment='left')\n",
    "\n",
    "\n",
    "plt.title('Actual RR vs Estimated RR - TMCH Dataset',fontsize=14)\n",
    "plt.xlabel('Actual Respiration Rate (bpm)',fontsize=14)\n",
    "plt.ylabel('Estimated Respiration Rate (bpm)',fontsize=14)\n",
    "plt.grid(\n",
    "    color='gray',        # Color of the grid lines\n",
    "    linestyle='-',      # Line style (e.g., '-', '--', '-.', ':')\n",
    "    linewidth=0.8,       # Line width\n",
    "    alpha=0.8            # Transparency of the grid\n",
    "    )\n",
    "plt.savefig(\"Actual RR vs Estimated RR - TMCH Dataset.png\", dpi=600, bbox_inches='tight')  # Adjust file name and format as needed\n",
    "plt.show()\n",
    "\n",
    "# 4. Error Analysis\n",
    "df['Error'] = df['Actual RR'] - df['Estimated RR']\n",
    "\n",
    "# RMSE, MAE, R²\n",
    "rmse = np.sqrt(mean_squared_error(df['Actual RR'], df['Estimated RR']))\n",
    "mae = mean_absolute_error(df['Actual RR'], df['Estimated RR'])\n",
    "r2 = r2_score(df['Actual RR'], df['Estimated RR'])\n",
    "\n",
    "# 8. Line plot of Actual vs Estimated RR over time (if index represents time/order)\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(df['Actual RR'], label='Actual RR', color='orange', marker='x')\n",
    "plt.plot(df['Estimated RR'], label='Estimated RR',color='blue', marker='o')\n",
    "plt.title('Actual vs Estimated RR(first 60 subjects) - TMCH Dataset',fontsize=14)\n",
    "plt.xlabel('No of Subjects',fontsize=14)\n",
    "plt.ylabel('Respiration Rate (bpm)',fontsize=14)\n",
    "plt.xlim(0,60)\n",
    "plt.grid(\n",
    "    color='gray',        # Color of the grid lines\n",
    "    linestyle='-',      # Line style (e.g., '-', '--', '-.', ':')\n",
    "    linewidth=0.9,       # Line width\n",
    "    alpha=0.9            # Transparency of the grid\n",
    "    )\n",
    "plt.legend(loc='upper right',\n",
    "    fontsize=12,\n",
    "    prop={'weight': 'bold'})\n",
    "\n",
    "plt.savefig(\"Actual vs Estimated RR(first 50 subjects) - TMCH Dataset.png\", dpi=600, bbox_inches='tight')  # Adjust file name and format as needed\n",
    "plt.show()\n",
    "\n",
    "print(f\"RMSE: {rmse}\")\n",
    "print(f\"MAE: {mae}\")\n",
    "print(f\"R²: {r2}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "657032bd-62f2-490b-8f38-98512d2c67eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "file_path = 'TMCH_Estimated_RR_v5.csv'  # Replace with your actual file path\n",
    "data = pd.read_csv(file_path)\n",
    "\n",
    "data.head()\n",
    "\n",
    "# Extract the calculated and numeric respiration rates\n",
    "calculated_respiration = data['Estimated RR']\n",
    "numeric_respiration = data['Actual RR']\n",
    "\n",
    "# Calculate differences and mean\n",
    "differences = calculated_respiration - numeric_respiration\n",
    "mean_values = (calculated_respiration + numeric_respiration) / 2\n",
    "\n",
    "# Calculate bias and limits of agreement\n",
    "bias = np.mean(differences)\n",
    "std_dev_diff = np.std(differences)\n",
    "loa_upper = bias + 1.96 * std_dev_diff\n",
    "loa_lower = bias - 1.96 * std_dev_diff\n",
    "\n",
    "# Prepare the plot\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(mean_values, differences, color='blue', alpha=0.5, label='Differences')\n",
    "\n",
    "# Set font properties for better visualization\n",
    "plt.rcParams['font.size'] = 14  # Default font size\n",
    "plt.rcParams['font.weight'] = 'bold'  # Bold font\n",
    "\n",
    "# Plot lines for bias and limits of agreement\n",
    "plt.axhline(bias, color='blue', linestyle='--', label='Bias = {:.2f}'.format(bias))\n",
    "plt.axhline(loa_upper, color='red', linestyle='--', label='95% Upper LoA = {:.2f}'.format(loa_upper))\n",
    "plt.axhline(loa_lower, color='red', linestyle='--', label='95% Lower LoA = {:.2f}'.format(loa_lower))\n",
    "\n",
    "# Set dynamic y-axis limits\n",
    "plt.ylim(differences.min() - 1, differences.max() + 1)\n",
    "\n",
    "plt.title('Bland-Altman Plot for RR - TMCH Dataset')\n",
    "plt.xlabel('Mean of Two Measurements',fontsize=14)\n",
    "plt.ylabel('Difference ',fontsize=14)\n",
    "plt.ylim(-10,10)\n",
    "plt.grid()\n",
    "plt.tight_layout()\n",
    "plt.legend()\n",
    "plt.grid(\n",
    "    color='gray',        # Color of the grid lines\n",
    "    linestyle='-',      # Line style (e.g., '-', '--', '-.', ':')\n",
    "    linewidth=0.9,       # Line width\n",
    "    alpha=0.9            # Transparency of the grid\n",
    "    )\n",
    "\n",
    "# Save the plot as an image file (optional)\n",
    "plt.savefig('TMCH_bland_altman_plot.png')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "19a8463b-aea4-4109-b4f7-38b0580d3e93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved: Bland_Altman_Plots/Bland_Altman_window_10s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_100s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_110s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_120s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_20s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_30s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_32s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_40s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_50s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_60s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_64s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_70s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_80s.png\n",
      "Saved: Bland_Altman_Plots/Bland_Altman_window_90s.png\n",
      "✅ All Bland-Altman plots generated successfully!\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import re\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Folder containing all CSV files (modify this path)\n",
    "folder_path = 'Respiration Windows Results/'  \n",
    "output_folder = 'Bland_Altman_Plots/'  # Output folder for saving plots\n",
    "\n",
    "# Create output folder if it doesn't exist\n",
    "os.makedirs(output_folder, exist_ok=True)\n",
    "\n",
    "# Get all CSV files in the folder\n",
    "csv_files = [f for f in os.listdir(folder_path) if f.endswith('.csv')]\n",
    "\n",
    "for file in csv_files:\n",
    "    file_path = os.path.join(folder_path, file)\n",
    "\n",
    "    # Extract window size using regex\n",
    "    match = re.search(r'window_(\\d+)', file)  # Looks for \"window_10\", \"window_120\", etc.\n",
    "    if match:\n",
    "        window_size = match.group(1)  # Extracts only the number\n",
    "    else:\n",
    "        print(f\"Skipping {file} (window size not found)\")\n",
    "        continue  # Skip files without proper naming\n",
    "\n",
    "    # Load CSV file\n",
    "    data = pd.read_csv(file_path)\n",
    "\n",
    "    # Compute Bland-Altman statistics\n",
    "    data['Difference'] = data['Actual RR'] - data['Estimated RR']\n",
    "    data['Average'] = (data['Actual RR'] + data['Estimated RR']) / 2\n",
    "\n",
    "    mean_diff = np.mean(data['Difference'])\n",
    "    std_diff = np.std(data['Difference'])\n",
    "\n",
    "    # Limits of Agreement (LoA)\n",
    "    loa_upper = mean_diff + 1.96 * std_diff\n",
    "    loa_lower = mean_diff - 1.96 * std_diff\n",
    "\n",
    "    # Generate Bland-Altman plot\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(data['Average'], data['Difference'], color='blue', alpha=0.5)\n",
    "    plt.axhline(mean_diff, color='black', linestyle='--', label='Mean Difference')\n",
    "    plt.axhline(loa_upper, color='red', linestyle='--', label='Upper LoA (1.96 SD)')\n",
    "    plt.axhline(loa_lower, color='red', linestyle='--', label='Lower LoA (-1.96 SD)')\n",
    "    plt.ylim(-10, 10)\n",
    "\n",
    "    # Formatting the title\n",
    "    plt.xlabel('Average RR', fontsize=14, fontweight='bold')\n",
    "    plt.ylabel('Difference (Actual RR - Estimated RR)', fontsize=14, fontweight='bold')\n",
    "    plt.title(f'Bland-Altman Plot - Window size: {window_size}s', fontsize=16, fontweight='bold')\n",
    "    \n",
    "    plt.legend(prop={'weight': 'bold', 'size': 12})\n",
    "    plt.grid(True)\n",
    "    \n",
    "    # Save Bland-Altman plot with proper naming\n",
    "    output_file = os.path.join(output_folder, f'Bland_Altman_window_{window_size}s.png')\n",
    "    plt.savefig(output_file, dpi=300, bbox_inches='tight')\n",
    "    \n",
    "    # Close plot to avoid memory issues in loops\n",
    "    plt.close()\n",
    "\n",
    "    print(f'Saved: {output_file}')\n",
    "\n",
    "print(\"✅ All Bland-Altman plots generated successfully!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "21ed8e0f-5253-4904-ad5c-33181305fc74",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Combined image saved as Bland_Altman_Combined.png\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from PIL import Image\n",
    "\n",
    "# Folder containing saved Bland-Altman plots\n",
    "input_folder = 'Bland_Altman_Plots/'\n",
    "output_file = 'Bland_Altman_Combined.png'  # Final combined image\n",
    "\n",
    "# Sort images based on window size in numerical order\n",
    "image_files = sorted(\n",
    "    [f for f in os.listdir(input_folder) if f.endswith('.png')],\n",
    "    key=lambda x: int(x.split('_')[-1].replace('s.png', ''))  # Extracts window size and sorts numerically\n",
    ")\n",
    "\n",
    "# Ensure we have exactly 12 images for a 4x3 grid\n",
    "if len(image_files) != 12:\n",
    "    print(f\"⚠ Expected 12 images, but found {len(image_files)}. Check the folder.\")\n",
    "    exit()\n",
    "\n",
    "# Load images\n",
    "images = [Image.open(os.path.join(input_folder, img)) for img in image_files]\n",
    "\n",
    "# Get size of a single image\n",
    "img_width, img_height = images[0].size\n",
    "\n",
    "# Create a blank canvas (4 images wide, 3 images tall)\n",
    "combined_img = Image.new('RGB', (img_width * 4, img_height * 3))\n",
    "\n",
    "# Paste images into the 4x3 grid\n",
    "for i, img in enumerate(images):\n",
    "    x_offset = (i % 4) * img_width  # Column position\n",
    "    y_offset = (i // 4) * img_height  # Row position\n",
    "    combined_img.paste(img, (x_offset, y_offset))\n",
    "\n",
    "# Save the combined image\n",
    "combined_img.save(output_file, dpi=(300, 300))\n",
    "print(f'✅ Combined image saved as {output_file}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "34fadd28-433f-4cff-a65e-40e402621828",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = \"window_performance_analysis_v5.csv\"  # Replace with your CSV file path\n",
    "data = pd.read_csv(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0e14b154-8b58-434f-b60d-836480c8f247",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Window Size (seconds)</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>R2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>3.309311</td>\n",
       "      <td>2.168834</td>\n",
       "      <td>-0.412792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>1.705970</td>\n",
       "      <td>1.245315</td>\n",
       "      <td>0.624555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>1.346614</td>\n",
       "      <td>0.981931</td>\n",
       "      <td>0.766068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32</td>\n",
       "      <td>1.255241</td>\n",
       "      <td>0.927725</td>\n",
       "      <td>0.796737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40</td>\n",
       "      <td>0.933744</td>\n",
       "      <td>0.734704</td>\n",
       "      <td>0.887524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>2.254745</td>\n",
       "      <td>1.415583</td>\n",
       "      <td>0.344160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>60</td>\n",
       "      <td>3.020007</td>\n",
       "      <td>2.194742</td>\n",
       "      <td>-0.176574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>64</td>\n",
       "      <td>3.201892</td>\n",
       "      <td>2.407648</td>\n",
       "      <td>-0.322563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>70</td>\n",
       "      <td>2.747137</td>\n",
       "      <td>2.101530</td>\n",
       "      <td>0.026438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>80</td>\n",
       "      <td>1.939830</td>\n",
       "      <td>1.454780</td>\n",
       "      <td>0.514566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>90</td>\n",
       "      <td>1.602448</td>\n",
       "      <td>1.216635</td>\n",
       "      <td>0.668739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>100</td>\n",
       "      <td>1.827918</td>\n",
       "      <td>1.352486</td>\n",
       "      <td>0.568961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>110</td>\n",
       "      <td>2.009022</td>\n",
       "      <td>1.461281</td>\n",
       "      <td>0.479318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>120</td>\n",
       "      <td>2.046849</td>\n",
       "      <td>1.494073</td>\n",
       "      <td>0.459526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Window Size (seconds)      RMSE       MAE        R2\n",
       "0                      10  3.309311  2.168834 -0.412792\n",
       "1                      20  1.705970  1.245315  0.624555\n",
       "2                      30  1.346614  0.981931  0.766068\n",
       "3                      32  1.255241  0.927725  0.796737\n",
       "4                      40  0.933744  0.734704  0.887524\n",
       "5                      50  2.254745  1.415583  0.344160\n",
       "6                      60  3.020007  2.194742 -0.176574\n",
       "7                      64  3.201892  2.407648 -0.322563\n",
       "8                      70  2.747137  2.101530  0.026438\n",
       "9                      80  1.939830  1.454780  0.514566\n",
       "10                     90  1.602448  1.216635  0.668739\n",
       "11                    100  1.827918  1.352486  0.568961\n",
       "12                    110  2.009022  1.461281  0.479318\n",
       "13                    120  2.046849  1.494073  0.459526"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "66f4a203-f9dc-4525-82f3-18a23488748e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.9337 bpm\n",
      "MAE: 0.7347 bpm\n",
      "R²: 0.8875\n",
      "Estimated RR - Standard Deviation: 2.6707 bpm\n",
      "Estimated RR - Variance: 7.1325 bpm²\n",
      "Error - Standard Deviation: 0.9336 bpm\n",
      "Error - Variance: 0.8717 bpm²\n",
      "RR (Mean ± SD): 15.40 ± 2.78 bpm\n",
      "RR (Min ± SD): 7.00 ± 2.78 bpm\n",
      "RR (Max ± SD): 26.90 ± 2.78 bpm\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "\n",
    "# Load the CSV file into a pandas DataFrame\n",
    "df = pd.read_csv('TMCH_Estimated_RR_v5.csv')  # Replace with your file path\n",
    "\n",
    "# Extract Actual RR and Estimated RR columns\n",
    "actual_rr = df['Actual RR']  \n",
    "estimated_rr = df['Estimated RR']  \n",
    "\n",
    "# Compute required statistics\n",
    "actual_mean = np.mean(actual_rr)\n",
    "actual_min = np.min(actual_rr)\n",
    "actual_max = np.max(actual_rr)\n",
    "actual_std = np.std(actual_rr)\n",
    "\n",
    "# Compute additional metrics\n",
    "rmse = np.sqrt(mean_squared_error(actual_rr, estimated_rr))\n",
    "mae = mean_absolute_error(actual_rr, estimated_rr)\n",
    "r2 = r2_score(actual_rr, estimated_rr)\n",
    "\n",
    "estimated_std = np.std(estimated_rr)\n",
    "estimated_variance = np.var(estimated_rr)\n",
    "\n",
    "# Error calculations\n",
    "error = actual_rr - estimated_rr\n",
    "error_variance = np.var(error)\n",
    "error_std = np.std(error)\n",
    "\n",
    "# Print results\n",
    "print(f'RMSE: {rmse:.4f} bpm')\n",
    "print(f'MAE: {mae:.4f} bpm')\n",
    "print(f'R²: {r2:.4f}')\n",
    "print(f'Estimated RR - Standard Deviation: {estimated_std:.4f} bpm')\n",
    "print(f'Estimated RR - Variance: {estimated_variance:.4f} bpm²')\n",
    "print(f'Error - Standard Deviation: {error_std:.4f} bpm')\n",
    "print(f'Error - Variance: {error_variance:.4f} bpm²')\n",
    "\n",
    "# Actual RR computed values\n",
    "print(f'RR (Mean ± SD): {actual_mean:.2f} ± {actual_std:.2f} bpm')\n",
    "print(f'RR (Min ± SD): {actual_min:.2f} ± {actual_std:.2f} bpm')\n",
    "print(f'RR (Max ± SD): {actual_max:.2f} ± {actual_std:.2f} bpm')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e34bf298-76fc-42f8-a338-4d69dc13a4c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "\n",
    "def estimate_respiration_rate(df, window_size):\n",
    "    # Placeholder function for respiration rate estimation logic\n",
    "    return df['Respiration Rate'].mean()  # Dummy estimation using mean value\n",
    "\n",
    "def process_files(folder_path, window_sizes):\n",
    "    overall_results = []\n",
    "    processing_times = []  # Store processing time for each subject and window\n",
    "\n",
    "    for window_size in window_sizes:\n",
    "        results = []\n",
    "        actual_rrs = []\n",
    "        estimated_rrs = []\n",
    "\n",
    "        for file in os.listdir(folder_path):\n",
    "            if file.endswith(\".csv\"):\n",
    "                file_path = os.path.join(folder_path, file)\n",
    "                df_data = pd.read_csv(file_path)\n",
    "\n",
    "                # Extract actual respiration rate\n",
    "                actual_rr = df_data['Respiration Rate'].mean()  # Average actual RR from the file\n",
    "                \n",
    "                # Start timing the estimation process\n",
    "                start_time = time.time()\n",
    "                estimated_rr = estimate_respiration_rate(df_data, window_size)\n",
    "                end_time = time.time()\n",
    "                \n",
    "                # Calculate processing time\n",
    "                processing_time = end_time - start_time\n",
    "                processing_times.append([file, window_size, processing_time])\n",
    "\n",
    "                # Append results\n",
    "                results.append([file, actual_rr, estimated_rr])\n",
    "\n",
    "                actual_rrs.append(actual_rr)\n",
    "                estimated_rrs.append(estimated_rr)\n",
    "\n",
    "        # Convert results to DataFrame\n",
    "        results_df = pd.DataFrame(results, columns=[\"Filename\", \"Actual RR\", \"Estimated RR\"])\n",
    "\n",
    "        # Calculate error metrics\n",
    "        rmse = np.sqrt(mean_squared_error(actual_rrs, estimated_rrs))\n",
    "        mae = mean_absolute_error(actual_rrs, estimated_rrs)\n",
    "        r2 = r2_score(actual_rrs, estimated_rrs)\n",
    "\n",
    "        # Store results for this window size\n",
    "        overall_results.append([window_size, rmse, mae, r2])\n",
    "\n",
    "        # Save respiration rate results for this window size\n",
    "        results_df.to_csv(f\"estimated_respiration_rates_window_{window_size}.csv\", index=False)\n",
    "\n",
    "    # Save overall results\n",
    "    overall_results_df = pd.DataFrame(overall_results, columns=[\"Window Size\", \"RMSE\", \"MAE\", \"R²\"])\n",
    "    overall_results_df.to_csv(\"window_performance_analysis.csv\", index=False)\n",
    "\n",
    "    # Save processing time details\n",
    "    processing_time_df = pd.DataFrame(processing_times, columns=[\"Filename\", \"Window Size\", \"Processing Time (seconds)\"])\n",
    "    processing_time_df.to_csv(\"processing_time_analysis.csv\", index=False)\n",
    "\n",
    "    print(\"Performance analysis completed. Results saved to 'window_performance_analysis.csv' and 'processing_time_analysis.csv'.\")\n",
    "\n",
    "# Define folder path and window sizes\n",
    "folder_path = \"TMNI_Dataset_Respiration/data_4/\"  # Update with the correct path\n",
    "window_sizes = [10, 20, 30, 40, 50]  # Define the window sizes you want to analyze\n",
    "\n",
    "# Run the function\n",
    "process_files(folder_path, window_sizes)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8c8f3dd1-26b8-4498-ac67-5a02b778e706",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ TMCH metrics with standard deviation and 95% CI saved to 'tmch_metrics_with_ci_per_window.csv'\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "from glob import glob\n",
    "\n",
    "# Function to compute metrics and statistical variability\n",
    "def compute_metrics(df):\n",
    "    n = len(df)\n",
    "    actual = df['Actual RR'].values\n",
    "    predicted = df['Estimated RR'].values\n",
    "\n",
    "    rmse = np.sqrt(mean_squared_error(actual, predicted))\n",
    "    mae = mean_absolute_error(actual, predicted)\n",
    "    r2 = r2_score(actual, predicted)\n",
    "\n",
    "    # Individual errors\n",
    "    errors_rmse = (predicted - actual) ** 2\n",
    "    errors_mae = np.abs(predicted - actual)\n",
    "\n",
    "    rmse_sd = errors_rmse.std(ddof=1)\n",
    "    mae_sd = errors_mae.std(ddof=1)\n",
    "\n",
    "    ci_95_rmse = 1.96 * rmse_sd / np.sqrt(n)\n",
    "    ci_95_mae = 1.96 * mae_sd / np.sqrt(n)\n",
    "\n",
    "    return {\n",
    "        'N': n,\n",
    "        'RMSE': rmse,\n",
    "        'RMSE_SD': rmse_sd,\n",
    "        'RMSE_CI': ci_95_rmse,\n",
    "        'MAE': mae,\n",
    "        'MAE_SD': mae_sd,\n",
    "        'MAE_CI': ci_95_mae,\n",
    "        'R2': r2\n",
    "    }\n",
    "\n",
    "# Directory where your 12 CSVs are stored\n",
    "data_dir = './Respiration Windows Results/'  # change this if files are in a different folder\n",
    "all_files = sorted(glob(os.path.join(data_dir, 'estimated_respiration_rates_window_*.csv')))\n",
    "\n",
    "results = []\n",
    "\n",
    "for file_path in all_files:\n",
    "    window_size = int(os.path.basename(file_path).split('_')[-1].replace('.csv', ''))\n",
    "    df = pd.read_csv(file_path)\n",
    "\n",
    "    # Compute metrics for TMCH\n",
    "    metrics = compute_metrics(df)\n",
    "    metrics['Window'] = window_size\n",
    "    results.append(metrics)\n",
    "\n",
    "# Combine and save results\n",
    "result_df = pd.DataFrame(results)\n",
    "result_df = result_df.sort_values('Window')\n",
    "\n",
    "# Save to CSV\n",
    "result_df.to_csv('tmch_metrics_with_ci_per_window.csv', index=False)\n",
    "\n",
    "print(\"✅ TMCH metrics with standard deviation and 95% CI saved to 'tmch_metrics_with_ci_per_window.csv'\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f32b546-6bee-4b2a-9c44-0fa5ea98001f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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